Evidence map›Paper›PMID 32363598›Full record

ArticleEpilepsia2020

Cognitive phenotypes in temporal lobe epilepsy utilizing data- and clinically driven approaches: Moving toward a new taxonomy.

Anny Reyes, Erik Kaestner, Lisa Ferguson, Jana E Jones, Michael Seidenberg, William B Barr, Robyn M Busch, Bruce P Hermann, Carrie R McDonald

Open access · greenAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Epilepsia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed
7.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 80 citations in OpenAlex.

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  10. A user's guide for the International Classification of Cognitive Disorders in Epilepsy.Epileptic disorders : international epilepsy journal with videotape · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 6 institutions in 1 country.

Anny ReyesSan Diego State University, University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.
Erik KaestnerCenter for Multimodal Imaging and Genetics, University of California, San Diego, CA, USA.
Lisa FergusonDepartment of Neurology, Cleveland Clinic, Cleveland, OH, USA.
Jana E JonesDepartment of Neurology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
Michael SeidenbergRosalind Franklin University of Medicine and Science, Chicago, IL, USA.
William B BarrDepartments of Neurology and Psychiatry, NYU-Langone Medical Center and NYU School of Medicine, New York, NY, USA.
Robyn M BuschDepartment of Neurology, Cleveland Clinic, Cleveland, OH, USA.
Bruce P HermannDepartment of Neurology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
Carrie R McDonaldSan Diego State University, University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA.
Cleveland Clinic · USUniversity of California, San Diego · USUniversity of Wisconsin–Madison · USNYU Langone Health · USRosalind Franklin University of Medicine and Science · USUniversity of California System · US

Funding

Fellowship on Biological Psychiatry and NeuroscienceT32MH018399 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Pei-an (Betty) Shih · 1986 to 2026
$7.3M
Multimodal Imaging of Language in the Preoperative Evaluation of EpilepsyR01NS065838 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCDONALD, CARRIE R · 2010 to 2018
$4.4M
Multimodal imaging of memory reorganization in epilepsy from whole brain networks to local neuronal responses: Implications for surgical-decision-makingR56NS065838 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCDONALD, CARRIE R · 2020 to 2020
$467k
Prediction of seizure lateralization and postoperative outcome through the use of deep learning applied to multi-site MRI/DTI data: An ENIGMA-Epilepsy studyR21NS107739 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI BONILHA, LEONARDO F, MCDONALD, CARRIE R · 2019 to 2019
$444k
Explaining cognitive heterogeneity in temporal lobe epilepsy (TLE): Identifying unique imaging features, health-related risk factors and protective factors in TLE subtypesF31NS111883 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI REYES, ANNY · 2019 to 2021
$89k
NIMH NIH HHS T32 MH018399NINDS NIH HHS F31 NS111883NINDS NIH HHS R01 NS065838NINDS NIH HHS R21 NS107739NINDS NIH HHS R56 NS065838
6 · The paper itself

Abstract

objectiveTo identify cognitive phenotypes in temporal lobe epilepsy (TLE) and test their reproducibility in a large, multi-site cohort of patients using both data-driven and clinically driven approaches.

methodFour-hundred seven patients with TLE who underwent a comprehensive neuropsychological evaluation at one of four epilepsy centers were included. Scores on tests of verbal memory, naming, fluency, executive function, and psychomotor speed were converted into z-scores based on 151 healthy controls (HCs). For the data-driven method, cluster analysis (k-means) was used to determine the optimal number of clusters. For the clinically driven method, impairment was defined as >1.5 standard deviations below the mean of the HC, and patients were classified into groups based on the pattern of impairment.

resultsCluster analysis revealed a three-cluster solution characterized by (a) generalized impairment (29%), (b) language and memory impairment (28%), and (c) no impairment (43%). Based on the clinical criteria, the same broad categories were identified, but with a different distribution: (a) generalized impairment (37%), (b) language and memory impairment (30%), and (c) no impairment (33%). There was a 82.6% concordance rate with good agreement (κ = .716) between the methods. Forty-eight patients classified as having a normal profile based on cluster analysis were classified as having generalized impairment (n = 16) or an isolated language/memory impairment (n = 32) based on the clinical criteria. Patients with generalized impairment had a longer disease duration and patients with no impairment had more years of education. However, patients demonstrating the classic TLE profile (ie, language and memory impairment) were not more likely to have an earlier age at onset or mesial temporal sclerosis. SIGNIFICANCE: We validate previous findings from single-site studies that have identified three unique cognitive phenotypes in TLE and offer a means of translating the patterns into a clinical diagnostic criteria, representing a novel taxonomy of neuropsychological status in TLE.

Indexed as

Neuropsychological TestsPhenotypeAdultClassificationCluster AnalysisCognitionDatabases, FactualEpilepsy, Temporal LobeFemaleHumansMaleMiddle AgedYoung Adultcognitive phenotypesepilepsytaxonomy

Identifiers

PMID32363598
PMCPMC7341371
OpenAlexW3023474630

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.